Zobrazeno 1 - 10 of 19 pro vyhledávání: '"Yukui Luo"'
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Akademický článek
A Novel FPGA Accelerator Design for Real-Time and Ultra-Low Power Deep Convolutional Neural Networks Compared With Titan X GPU
Autor: Shuai Li, Yukui Luo, Kuangyuan Sun, Nandakishor Yadav, Kyuwon Ken Choi
Publikováno v: IEEE Access, Vol 8, Pp 105455-105471 (2020)
Convolutional neural networks (CNNs) based deep learning algorithms require high data flow and computational intensity. For real-time industrial applications, they need to overcome challenges such as high data bandwidth requirement and power consumpt
Externí odkaz: https://doaj.org/article/dcd2360477d3470883441cefc2b50db7
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3
A High-Performance and Secure TRNG Based on Chaotic Cellular Automata Topology
Autor: Scott C. Best, Yanzhi Wang, Xiaolin Xu, Wenhao Wang, Yukui Luo
Publikováno v: IEEE Transactions on Circuits and Systems I: Regular Papers. 67:4970-4983
As an important hardware security primitive, the true random number generator (TRNG) has been widely utilized in many critical applications. The performance and security of TRNGs are always dominant features that determine the usability of a TRNG sch
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d540ca7f9b37bd07be595cbb915ca670
https://doi.org/10.1109/tcsi.2020.3019030
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5
SGX-FPGA: Trusted Execution Environment for CPU-FPGA Heterogeneous Architecture
Autor: Sheng Wei, Ke Xia, Xiaolin Xu, Yukui Luo
Publikováno v: DAC
Trusted execution environments (TEEs), such as Intel SGX, have become a popular security primitive with minimum trusted computing base (TCB) and attack surface. However, the existing CPU-based TEEs do not support FPGAs, even though FPGA-based cloud c
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::525f5c2df391d8686dcc4cf4e9df1064
https://doi.org/10.1109/dac18074.2021.9586207
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8
A Novel FPGA Accelerator Design for Real-Time and Ultra-Low Power Deep Convolutional Neural Networks Compared With Titan X GPU
Autor: Nandakishor Yadav, Yukui Luo, Shuai Li, Kyuwon Ken Choi, Kuangyuan Sun
Publikováno v: IEEE Access, Vol 8, Pp 105455-105471 (2020)
Convolutional neural networks (CNNs) based deep learning algorithms require high data flow and computational intensity. For real-time industrial applications, they need to overcome challenges such as high data bandwidth requirement and power consumpt
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b3624c20ccbe9dac0536b9f32eca59d5
https://ieeexplore.ieee.org/document/9108269/
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9
A Survey of Recent Attacks and Mitigation on FPGA Systems
Autor: Yukui Luo, Shijin Duan, Xiaolin Xu, Wenhao Wang
Publikováno v: ISVLSI
The emergence of a large variety of compute-intensive applications has made hardware accelerators a new necessity to deploy the corresponding high-complexity algorithms, such as the Deep Neural Network (DNN). Thanks to the flexibility from hardware r
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::dadfdb754026dd619ffe0972e7a595b8
https://doi.org/10.1109/isvlsi51109.2021.00059
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10
DeepStrike: Remotely-Guided Fault Injection Attacks on DNN Accelerator in Cloud-FPGA
Autor: Yunsi Fei, Yukui Luo, Cheng Gongye, Xiaolin Xu
Publikováno v: DAC
As Field-programmable gate arrays (FPGAs) are widely adopted in clouds to accelerate Deep Neural Networks (DNN), such virtualization environments have posed many new security issues. This work investigates the integrity of DNN FPGA accelerators in cl
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f19fce1b0292f6f81863f7daeeab6d41
http://arxiv.org/abs/2105.09453
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